Not applicable.
Not applicable.
The present invention relates to multi-slice helical computerized tomography and more particularly to a tomography algorithm, method and apparatus which reduces the data acquisition time and data processing time required to generate an image while maintaining high image quality.
In computerized tomography (CT) X-ray photon rays are directed through a patient toward a detector. Attenuated rays are detected by the detector, the amount of attenuation indicative of the make up (e.g. bone, flesh, air pocket, etc.) of the patient through which the rays traversed. The attenuation data is then processed and back-projected according to a reconstruction algorithm to generate an image of the patient""s internal anatomy. Generally, the xe2x80x9cback-projectionxe2x80x9d is performed in software but, as the name implies, is akin to physically projecting rays from many different angles within an image plane through the image plane, the values of rays passing through the same image voxels being combined in some manner to have a combined effect on the voxel in the resulting image. Hereinafter the data corresponding to rays which are back-projected will be referred to as back-projection rays.
During data acquisition, if a patient moves, artifacts can occur in the resulting image which often render images useless or difficult to use for diagnostics purposes. For this and other reasons the CT industry is constantly trying to identify ways to reduce the duration of acquisition periods without reducing the quality of the data acquired.
Various CT system features and procedures have been developed to increase data acquisition speed. Some of the more popular features and procedures including fan beam acquisition, simultaneous multiple slice acquisition, helical scanning and half-scanning. In fan beam acquisition the source is collimated into a thin fan beam which is directed at a detector on a side opposite a patient. In this manner, a complete fan beam projection data set is instantaneously generated for a beam angle defined by a central ray of the source fan beam. The source and detector are rotated about an image plane to collect data from all (e.g., typically 360 degrees) beam angles. Thereafter the collected data is used to reconstruct an image in the image plane. Thus, fan beam acquisition reduces acquisition period duration.
With respect to half-scanning, assuming a patient remains still during a data acquisition period, conjugate data acquisitions (i.e., data acquired along the same path from opposite directions) should be identical. In addition, using a fan beam, at least one ray can be directed through an image plane from every possible beam angle without having to perform a complete rotation about the patient. To this end, as known in the industry, data corresponding to every beam angle associated with a single image plane can be collected after a (xcfx80+2xcex3)/2xcfx80 rotation about the patient where xcex3 is the fan beam angle. Because less than an entire rotation about a patient is required to acquire data corresponding to a slice image, these acquisition methods and systems are generally referred to as half-scan methods and systems. Thus, half-scan acquisition has been employed to reduce acquisition period duration in conjunction with single row detectors.
Single slice detectors, fan beams and half-scans can be used to generate data in several different parallel image planes which, after data acquisition, can be used by a processor to generate an image anywhere between the image planes through interpolation/extrapolation procedures known in the art. For example, assume that during two data acquisition periods first and second data sets were acquired which correspond to first and second parallel acquisition planes, respectively, the planes separated by 0.25 inches. If a user selects an image plane for reconstructing an image which resides between the first and second acquisition planes, interpolation between data in the first and second sets can be used to estimate values of data corresponding to the selected image plane. For instance, assume that, among other rays, during the acquisition periods a first ray and a second ray were used to generate data in the first and second sets, respectively, and that the first and second rays were parallel (i.e. had the same beam and fan angles). In this case, by interpolating between the data acquired from the first and second rays generates an estimated value corresponding to a hypothetical back-projection ray which is parallel to the first and second rays and which is within the image plane. By performing such interpolation to generate back-projection rays for every beam and fan angle through the image plane a complete data set corresponding to the image plane is generated.
While such systems work, unfortunately, the acquisition time required to generate data corresponding to many image planes is excessive and inevitable patient movement often causes image artifacts.
One way to speed up data acquisition corresponding to several image planes is by employing a multi-row detector with a fan beam. In multi-row detector systems, a relatively thick fan beam is collimated and directed through a patient at a multi-row detector, each detector row in effect gathering data for a separate xe2x80x9cslicexe2x80x9d of the thick fan beam along the Z or translation axis perpendicular to a fan beam width. Despite each detector row having a thickness, in these systems it is assumed that the detected signals in each row correspond to a plane centered within the row as projected onto the isocenter Z. Hereinafter the central plane through a row will be referred to as a row center.
After data acquisition an interface enables a system user to select an image plane from within the area corresponding to the collected data. The selected image plane is between the row centers of at least two adjacent detector rows. After image plane selection, a processor interpolates between data corresponding to adjacent rows to generate back-projection rays corresponding to the selected image plane. When another image corresponding to a different image plane is desired, after selecting the plane, the processor again identifies an acquired data subset for interpolation, additional processing and back-projection. Thus, multi-row detector systems further reduce data acquisition period duration where several image planes may be selected for reconstruction.
One limitation with multi-row detectors is that, during a single acquisition period, data can only be collected which corresponds to the detector thickness. To collect additional data corresponding to a greater patient volume or region of interest (ROI), after one acquisition period corresponding to a first volume, the patient has to be moved along a translation axis until a second volume which is adjacent the first volume is between the source and detector. Thereafter a second acquisition process has to be performed. Similarly, to collect additional data corresponding to a third volume the patient has to be transported to another relative location with respect to the source and detector. Required translation without acquisition necessarily prolong the acquisition period and the additional acquisition time and aligning processes inevitably result in relative discomfort, additional patient movements and undesirable image artifacts.
Helical scanning systems have been developed so that data can be collected during a single acquisition period without halting patient translation during the acquisition period. In a helical scanning system, the source and detector array are mounted on opposing surfaces of an annular gantry and are rotated there around as a patient is transported at constant speed through the gantry. The X-ray beam sweeps a helical path through the patient, hence the nomenclature xe2x80x9chelical scanning systemxe2x80x9d. Data acquisition can be sped up by increasing operating pitch (i.e., table translation speed relative to gantry rotation rate). After data is acquired the data is processed to generate back-projection ray estimates and account for data nuances which are caused by the helical acquisition.
Various combinations of the fan-beam, multi-slice, half-scan and helical scanning features have been combined to realize synergies and have been somewhat successful. For example, one system combines a multi-row fan beam detector and a fan beam source with a helical scanning procedure to rapidly acquire imaging data using a high pitch/high speed mode of operation. For example, U.S. Pat. No. 5,541,970 (hereinafter xe2x80x9cthe ""970 patentxe2x80x9d) which issued on Jul. 30, 1996 and is entitled xe2x80x9cImage Reconstruction for a CT System Implementing Four Fan Beam Helical Scanxe2x80x9d teaches an exemplary system including a four row detector where, during acquisition, helical data is collected about an ROI for each of the four rows. The collected data includes xe2x80x9cviewsxe2x80x9d where each view includes the data corresponding to the entire detector that is collected from a specific source angle about the gantry. Hereinafter, the phrase xe2x80x9crow viewxe2x80x9d will be used to identify the data corresponding to a specific detector row acquired at a specific gantry angle so that a four row detector will have first, second, third and fourth separate row views at each gantry angle.
After data has been collected and stored, when a system operator identifies a transaxial plane through the ROI at which a required image is to be generated, a system processor selects a sub-set of the helical data (hereinafter xe2x80x9ca selected data subsetxe2x80x9d) which is, in effect, centered on the selected plane. Thereafter, the selected data sub-set is altered to generate slice image data corresponding to the slice image plane, the altered data is filtered and back-projected across the slice image plane to generate the desired image for viewing and further processing. In order to generate a high quality image, the back-projected data must include views from many equi-spaced gantry angles about the slice plane.
In order to convert the selected data sub-set into slice image data for filtering and back-projection, the selected data sub-set including data from all four detector rows is weighted according to an algorithm that is spatially dependent along the Z or translation axis. To this end, for each detector row, at least one row view will typically be aligned with the slice image plane and therefore can be used for imaging purposes in its acquired state (i.e., without weighting). Hereinafter the gantry angle corresponding to an aligned row view will be referred to as an aligned angle.
For each remaining gantry angle in the slice image plane there are other row views within the selected data sub-set proximate the imaging plane. For instance, in the case of a four row detector, for gantry angles that are similar to the aligned angle, the selected data set will include two row views preceding the image plane and two row views following the image plane. For other gantry angles that are less similar to the aligned angle the selected data set will include either one row view preceding the image plane and three row views following the image plane or vice versa.
In any event, for each remaining gantry angle (i.e., all gantry angles that are not aligned with the slice image plane) in the slice image plane, the proximate row views are weighted generally as a function of spacing along the Z-axis. For instance, for a given gantry angle where the slice image plane is between second and third detector row views and is closer to the second row view than the third row view, the row view weightings from highest to lowest are second, third, first and fourth, respectively. After each row view within the selected data sub-set is weighted, the weighted data is filtered and back-projected to generate the required image. In this manner, a full set of weighted views is created to perform a conventional 360xc2x0 CT reconstruction.
While the algorithm described in the ""970 patent works well for four row detectors, unfortunately, when larger detectors are designed to collect additional rows of data (e.g., eight row detectors), it has been found that a higher helical pitch (i.e., table translation speed relative to gantry rotation rate) and larger cone angles (i.e., the angles between X-ray beams within the Z or translation axis) result which cause image artifacts and appreciably adversely affect the diagnostic value of resulting images.
The present invention includes a new weighting algorithm and method that can be used with detectors having virtually any number of detector element rows to generate highly accurate images from helically scanned CT data. The inventive algorithm generally includes two sequential weighting processes. First, after helically scanned data has been collected for a region of interest (ROI) and a transaxial slice image plane through the ROI has been identified, a sub-set of data corresponding to the selected slice image plane is identified and then a helical weighting algorithm is applied separately to the data corresponding to each of the detector rows to generate a separate helical weighted array for each detector row. For instance, where a detector includes eight detector rows, eight separate helical weighted arrays are generated.
Importantly, referring to FIG. 5 where an exemplary inventive weighting function is illustrated in two dimensions, the inventive weighting function applied to each row view is both gantry angle xcex2 and beam angle xcex3 dependent. To this end, along line 130 the weighting function has a value of one, along each of lines 131 and 132 the weighting function has a value of zero and between lines 131 and 130 and lines 132 and 130 the weighting function slopes from zero to one. The slope of lines 130, 131 and 130 is referred to generally as a tangent weighting parameter tg which, after system pitch and detector width are set, can be modified through an optimization process until optimal imaging characteristics result (e.g., artifacts and noise are minimized).
Second, after the helical weighting function has been applied and helical weighted arrays for each row have been generated, a conjugate weighting function is applied to each helical weighted array thereby generating a separate conjugate weighted array for each detector row.
After conjugate weighting is applied the resulting conjugate weighted arrays are filtered and back-projected thereby generating a slice image corresponding to the selected slice image plane. The conjugate weighted arrays may be combined before filtering and back-projection or the filtering and back-projection may be performed on a row by row basis to generate row specific slice images which are then combined to generate a final or combined slice image.
These and other aspects of the invention will become apparent from the following description. In the description, reference is made to the accompanying drawings which form a part hereof, and in which there is shown a preferred embodiment of the invention. Such embodiment does not necessarily represent the full scope of the invention and reference is made therefore, to the claims herein for interpreting the scope of the invention.